Free Access
Aquat. Living Resour.
Volume 32, 2019
Article Number 20
Number of page(s) 11
Published online 26 August 2019
  • Arrizabalaba H, de Bruyn P, Diaz GA, Murua H, Chavance P, Delgado de Molina A, Gaertner D, Ariz J, Ruiz J, Kell LT. 2011. Productivity and susceptibility analysis for species caught in Atlantic tuna fisheries. Aquat Living Resour 24: 1–12. [CrossRef] [EDP Sciences] [Google Scholar]
  • Christensen V, Pauly D. 1992. ECOPATH II − a software for balancing steady-state ecosystem models and calculating network characteristics. Ecol Model 61: 169–185. [CrossRef] [Google Scholar]
  • Cope JM, DeVore J, Dick EJ, Ames K, Budrick J, Erickson DL, Grebel J, Hanshew G, Jones R, Mattes L, Niles C, Williams S. 2011. An approach to defining stock complexes for U.S. West Coast Groundfishes using vulnerabilities and ecological distributions. N Am J Fish Manag 31: 589–604. [CrossRef] [Google Scholar]
  • Cortés E. 2000. Life history patterns and correlations in sharks. Rev Fish Sci 8: 299–344. [CrossRef] [Google Scholar]
  • Croll DA, Tershy BR, Newton KM, de Vos A, Hazen E, Goldbogen JA. 2018. Filter feeding. In: B. Würsig, J.G.M. Thewissen, K.M. Kovacs, (Eds.), Encyclopedia of Marine Mammals, Third Edition, Academic Press, pp. 363–368. [CrossRef] [Google Scholar]
  • Denney NH, Jennings S, Reynolds JD. 2002. Life-history correlates of maximum population growth rates in marine fishes. Proc R Soc Lond [Biol] 269: 2229–2237. [CrossRef] [PubMed] [Google Scholar]
  • Dillingham PW, Moore JE, Fletcher D, Cortés E, Curtis KA, James KC, Lewison RL. 2016. Improved estimation of intrinsic growth r max for long-lived species: integrating matrix models and allometry. Ecol Appl 26: 322–333. [CrossRef] [PubMed] [Google Scholar]
  • Duffy LM, Lennert-Cody CE, Olson R, Minte-Vera CV, Griffiths SP. 2019. Assessing vulnerability of bycatch species in the tuna purse-seine fisheries of the eastern Pacific Ocean. Fish Res doi: [Google Scholar]
  • Fletcher WJ. 2005. The application of qualitative risk assessment methodology to prioritise issues for fisheries management. ICES J Mar Sci 62: 1576–1587. [CrossRef] [Google Scholar]
  • Froese R, Binohlan C. 2000. Empirical relationships to estimate asymptotic length, length at first maturity and length at maximum yield per recruit in fishes, with a simple method to evaluate length frequency data. J Fish Biol 56: 758–773. [CrossRef] [Google Scholar]
  • Griffiths SP, Brewer DT, Heales DS, Milton DA, Stobutzki IC. 2006. Validating ecological risk assessments for fisheries: assessing the impacts of turtle excluder devices on elasmobranch bycatch populations in an Australian trawl fishery. Mar Freshwater Res 57: 395–401. [CrossRef] [Google Scholar]
  • Griffiths SP, Kesner-Reyes K, Garilao CV, Duffy L, Roman M. 2018. Development of a flexible ecological risk assessment (ERA) approach for quantifying the cumulative impacts of fisheries on bycatch species in the eastern Pacific Ocean. SAC-09-12 Inter-American Tropical Tuna Commission Scientific Advisory Committee Ninth Meeting. 14–18 May 2018. [Google Scholar]
  • Hobday AJ, Smith A, Webb R, Daley R, Wayte S, Bulman C, Dowdney J, Williams A, Sporcic M, Dambacher J, Fuller M, Walker T. 2007. Ecological Risk Assessment for the Effects of Fishing: Methodology. Report R04/1072 for the Australian Fisheries Management Authority, Canberra, pp. 174. [Google Scholar]
  • Jennings S, Reynolds JD, Mills SC. 1998. Life history correlates of responses to fisheries exploitation. Proc R Soc Lond [Biol] 265: 333–339. [CrossRef] [Google Scholar]
  • Kirby DS. 2006. Ecological risk assessment for species caught in WCPO tuna fisheries: inherent risk as determined by productivity-susceptibility analysis. WCPFC-SC-2006/EB WP-1, 24 p. [Google Scholar]
  • Lucena Frédou F, Frédou T, Gaetner D, Kell L, Potier M, Bach P, Travassos P, Hazin F, Ménard F. 2016. Life history traits and fishery patterns of teleosts caught by the tuna longline fishery in the South Atlantic and Indian Oceans. Fish Res 179: 308–321. [CrossRef] [Google Scholar]
  • Lucena Frédou F, Kell L, Frédou T, Gaetner D, Potier M, Bach P, Travassos P, Hazin F, Ménard F. 2017. Vulnerability of teleosts caught by the pelagic longline fleets in South Atlantic and Western Indian Oceans. Deep Sea Res (II Top. Stud. Oceanogr.) 140: 230–241. [CrossRef] [Google Scholar]
  • Milton DA. 2001. Assessing the susceptibility to fishing of populations of rare trawl bycatch: sea snakes caught by Australia's Northern Prawn Fishery. Biol Conserv 101: 281–290. [CrossRef] [Google Scholar]
  • Musick JA. 1999. Criteria to define extinction risk in marine fishes. Fisheries 24: 6–14. [CrossRef] [Google Scholar]
  • Pardo SA, Kindsvater HK, Reynolds JD, Dulvy ND. 2016. Maximum intrinsic rate of population increase in sharks, rays, and chimaeras: the importance of survival to maturity. Can J Fish Aquat Sci 73: 1159–1163. [CrossRef] [Google Scholar]
  • Pascual MA, Iribarne OO. 1993. How good are empirical predictions of natural mortality? Fish Res 16: 17–24. [CrossRef] [Google Scholar]
  • Patrick WS, Spencer P, Link J, Cope J, Field J, Kobayashi D, Lawson P, Gedamke T, Cortés E, Ormseth O, Bigelow K, Overholtz W. 2010. Using productivity and susceptibility indices to assess the vulnerability of United States fish stocks to overfishing. Fish Bull 108: 305–322. [Google Scholar]
  • Patrick WS, Spencer P, Ormseth O, Cope J, Field J, Kobayashi D, Gedamke T, Cortés E, Bigelow K, Overholtz W, Link J, Lawson P. 2009. Use of productivity and susceptibility indices to determine stock vulnerability, with example applications to six U.S. Fisheries. U.S. Dep. Commer., NOAA Tech Memo. NMFS-F/SPO-101. 90 pp. [Google Scholar]
  • Pauly D. 1980. On the interrelationship between natural mortality, growth parameters, and mean environmental temperature in 175 fish stocks. J Con Int Explor Mer 39: 175–192. [CrossRef] [Google Scholar]
  • Pauly D, Trites AW, Capuli E, Christensen V. 1998. Diet composition and trophic levels of marine mammals. ICES J Mar Sci 55: 467–481. [CrossRef] [Google Scholar]
  • R Development Core Team. 2017. R: A language and environment for statistical computing. Vienna, Austria, URL, R Foundation for Statistical Computing. [Google Scholar]
  • Stobutzki IC, Miller M, Brewer D. 2001. Sustainability of fishery bycatch: a process for assessing highly diverse and numerous bycatch. Environ Conserv 28: 167–181. [CrossRef] [Google Scholar]
  • Then AY, Hoenig JM, Hall NG, Hewitt DA. 2015. Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species. ICES J Mar Sci 72: 82–92. [CrossRef] [Google Scholar]
  • Thorson JT, Munch SB, Cope JM, Gao J. 2017. Predicting life history parameters for all fishes worldwide. Ecol Appl 27: 2262–2276. [CrossRef] [PubMed] [Google Scholar]
  • Walker TI. 2005. 13. Management measures. In: J. Musick, R. Bonfil, (Eds.), Management techniques for elasmobranch fisheries. FAO Fisheries Technical Paper. No. 474. Rome, FAO, pp. 216–242. [Google Scholar]
  • Zhou S, Griffiths SP. 2006. Sustainability Assessment for Fishing Effects (SAFE): an application to diverse elasmobranch bycatch in a tropical Australian prawn trawl fishery. In: D. Brewer, S.P. Griffiths, D.S. Heales et al. (Eds.), Design, trial and implementation of an integrated, long-term bycatch monitoring program, road tested in the NPF, Final Report on FRDC Project 2004/024 CSIRO Marine and Atmospheric Research, Cleveland, pp. 179–207. [Google Scholar]
  • Zhou S, Yin S, Thorson JT, Smith ADM, Fuller M. 2012. Linking fishing mortality reference points to life history traits: an empirical study. Can J Fish Aquat Sci 69: 1292–1301. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.